Video content analysis (also Video content analytics, VCA) is the capability to automatically analyze video to detect and determine temporal and spatial events. As such, it can be seen as the automated equivalent of the biological visual cortex.
This technical capability is used in a wide range of domains, including entertainment, health-care, retail, automotive, transport, home automation, safety and security. The algorithms can be implemented as software on general purpose machines, or as hardware in specialized video processing units.
Many different functionalities can be implemented in VCA. Video Motion Detection is one of the simpler forms where motion is detected with regard to a fixed background scene. More advanced functionalities include video tracking and egomotion estimation.
Based on the internal representation that VCA generates in the machine, it is possible to build other functionalities, such as identification, behavior analysis or other forms of situation awareness.
VCA relies on good input video, so it is often combined with video enhancement technologies such as video denoising, image stabilization, unsharp masking and super-resolution.
Still, there remains a need, in the fields of computer vision, image and video analysis, and scene capture and registration, for technologies that may utilize multi factor image feature registration and tracking, including both static and dynamic parameters within a video feed, and optionally acoustically acquired scene information.